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Copy pathFarrayTypes.cpp
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288 lines (280 loc) · 6.59 KB
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# include "FarrayTypes.h"
// A constructor
Rfarray :: Rfarray()
{
N = 0;
g = 0.0;
}
// A function that generates a random floating point array based on distribution
void Rfarray :: generate(int n, int d, Timer &t1, float l, float r)
{
FileOp :: fixOutprecision(fout);
default_random_engine generator(system_clock :: now().time_since_epoch().count());
if(d == 0)
{
uniform_real_distribution <float> distribution(l, r);
g = distribution(generator);
for(int i = 0; i < n; i++)
{
fout << g << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 1)
{
g = l;
for(int i = 0; i < n; i++)
{
fout << g << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 2)
{
g = r;
for(int i = 0; i < n; i++)
{
fout << g << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 3)
{
uniform_real_distribution <float> distribution(l, r);
for(int i = 0; i < n; i++)
{
g = distribution(generator);
fout << g << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 4)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
float sd = sqrt((mean - l) * (r - mean));
normal_distribution <float> distribution(mean, sd);
for(int i = 0; i < n; i++)
{
g = distribution(generator);
fout << l + fmod(g, (r - l + 1)) << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 5)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
float cnt = sqrt((mean - l) * (r - mean));
gamma_distribution <float> distribution(mean, cnt);
for(int i = 0; i < n; i++)
{
g = distribution(generator);
fout << l + fmod(g, (r - l + 1))<< " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 6)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
exponential_distribution <float> distribution(1.0 / mean);
for(int i = 0; i < n; i++)
{
g = distribution(generator);
fout << l + fmod(g, (r - l + 1)) << " \n"[i == n - 1];
t1.time(1);
}
}
else if(d == 9)
{
uniform_real_distribution <float> d1(l, r);
float mid = d1(generator);
array <float, 3> intervals {l * 1.0, mid, r * 1.0};
array <float, 3> weights {10.0, 1.0, 10.0};
piecewise_linear_distribution <float> distribution(intervals.begin(), intervals.end(), weights.begin());
for(int i = 0; i < n; i++)
{
g = distribution(generator);
fout << g << " \n"[i == n - 1];
t1.time(1);
}
}
}
// A function that generates floating point array test case files
void Rfarray :: setCase(string &s, int T, int t, int n, float l, float r, int d, bool neg, int sz, string &folder_name)
{
int pt = FileOp :: printT(t);
cout << "Generating farray test files: " << '\n';
for(int i = 0; i < T; i++)
{
FileOp :: setFile(folder_name, s, i, fout);
vector <int> times = numOp :: giveRints(t, n, sz);
N = times.size();
if(pt)
fout << N << '\n';
int tcnt = 0;
for(int j = 0; j < N; j++)
tcnt += times[j];
Timer t1(tcnt);
vector <int> dist = setCaseDist(N, d, neg);
for(int j = 0; j < N; j++)
{
fout << times[j] << '\n';
generate(times[j], dist[j], t1, l, r);
}
fout.close();
}
cout << "farray generation completed." << '\n';
}
// A function that sets distribution for all test cases
vector <int> Rfarray :: setCaseDist(int n, int d, bool neg)
{
Distribution d1;
vector <int> dist;
d1.setCaseDis(n, d, dist, (float)1.5, neg);
return dist;
}
// A constructor
Rsfarray :: Rsfarray()
{
N = 0;
rn = 0.0;
default_random_engine generator(system_clock :: now().time_since_epoch().count());
}
// A function that generates a sorted floating point array
void Rsfarray :: generate(int n, int d, Timer &t1, float l, float r)
{
FileOp :: fixOutprecision(fout);
g.clear();
if(d == 0)
{
uniform_real_distribution <float> distribution(l, r);
rn = distribution(generator);
for(int i = 0; i < n; i++)
{
g.push_back(rn);
t1.time(1);
}
}
else if(d == 1)
{
rn = l;
for(int i = 0; i < n; i++)
{
g.push_back(rn);
t1.time(1);
}
}
else if(d == 2)
{
rn = r;
for(int i = 0; i < n; i++)
{
g.push_back(rn);
t1.time(1);
}
}
else if(d == 3)
{
uniform_real_distribution <float> distribution(l, r);
for(int i = 0; i < n; i++)
{
rn = distribution(generator);
g.push_back(rn);
t1.time(1);
}
}
else if(d == 4)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
float sd = sqrt((mean - l) * (r - mean));
normal_distribution <float> distribution(mean, sd);
for(int i = 0; i < n; i++)
{
rn = distribution(generator);
g.push_back(l + fmod(rn, (r - l + 1)));
t1.time(1);
}
}
else if(d == 5)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
float cnt = sqrt((mean - l) * (r - mean));
gamma_distribution <float> distribution(mean, cnt);
for(int i = 0; i < n; i++)
{
rn = distribution(generator);
g.push_back(l + fmod(rn, (r - l + 1)));
t1.time(1);
}
}
else if(d == 6)
{
uniform_real_distribution <float> d1(l, r);
float mean = d1(generator);
exponential_distribution <float> distribution(1.0 / mean);
for(int i = 0; i < n; i++)
{
rn = distribution(generator);
g.push_back(l + fmod(rn, r - l + 1));
t1.time(1);
}
}
else if(d == 9)
{
uniform_real_distribution <float> d1(l, r);
float mid = d1(generator);
array <float, 3> intervals {l * 1.0, mid, r * 1.0};
array <float, 3> weights {10.0, 1.0, 10.0};
piecewise_linear_distribution <float> distribution(intervals.begin(), intervals.end(), weights.begin());
for(int i = 0; i < n; i++)
{
rn = distribution(generator);
g.push_back(rn);
t1.time(1);
}
}
}
// A function that generates sorted floating point array test case files
void Rsfarray :: setCase(string &s, int T, int t, int n, float l, float r, int d, bool neg, int sz, string &folder_name)
{
int pt = FileOp :: printT(t);
cout << "Generating sfarray test files: " << '\n';
for(int i = 0; i < T; i++)
{
FileOp :: setFile(folder_name, s, i, fout);
vector <int> times = numOp :: giveRints(t, n, sz);
N = times.size();
if(pt)
fout << N << '\n';
int tcnt = 0;
for(int j = 0; j < N; j++)
tcnt += times[j];
Timer t1(2 * tcnt);
vector <int> dist = setCaseDist(N, d, neg);
for(int j = 0; j < N; j++)
{
fout << times[j] << '\n';
generate(times[j], dist[j], t1, l, r);
sort(g.begin(), g.end());
for(int k = 0; k < (int)g.size(); k++)
{
fout << g[k] << " \n"[i == n - 1];
t1.time(1);
}
}
fout.close();
}
cout << "sfarray generation completed." << '\n';
}
// A function that sets distribution for all test cases
vector <int> Rsfarray :: setCaseDist(int n, int d, bool neg)
{
Distribution d1;
vector <int> dist;
d1.setCaseDis(n, d, dist, (float)1.5, neg);
return dist;
}